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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

PMU and Communication Infrastructure Restoration for Post-Attack Observability Recovery of Power Grids

This paper is concerned about recovering the observability of cyber-physical power grids after massive cyber attacks, which helps to achieve the cyber-physical resilience of the grids. For recovering the observability of the grid, the measurability of the Phasor Measurement Units (PMUs) and the connectivity of the communication network are needed to be restored. The PMU and communication infrastructure restoration problem is jointly formulated as a Mixed Integer Linear Programming (MILP) problem to minimize the observability loss of the grid over time after a cyber attack while considering the constraint of limited resources. The efficacy of the proposed optimal restoration strategy is verified by comparing with heuristic methods on the IEEE 57-bus system.

cyber security↗
DOE OSTI2024

Multi-Agent Graph-Attention Deep Reinforcement Learning for Post-Contingency Grid Emergency Voltage Control

Grid emergency voltage control (GEVC) is paramount in electric power systems to improve voltage stability and prevent cascading outages and blackouts in case of contingencies. While most deep reinforcement learning (DRL)-based paradigms perform single agents in a static environment, real-world agents for GEVC are expected to cooperate in a dynamically shifting grid. Moreover, due to high uncertainties from combinatory natures of various contingencies and load consumption, along with the complexity of dynamic grid operation, the data efficiency and control performance of the existing DRL-based methods are challenged. To address these limitations, we propose a multi-agent graph-attention (GATT)-based DRL algorithm for GEVC in multi-area power systems. Here, we develop graph convolutional network (GCN)-based agents for feature representation of the graph-structured voltages to improve the decision accuracy in a data-efficient manner. Furthermore, a cutting-edge attention mechanism concentrates on effective information sharing among multiple agents, synergizing different-sized subnetworks in the grid for cooperative learning. We address several key challenges in the existing DRL-based GEVC approaches, including low scalability and poor stability against high uncertainties. Test results in the IEEE benchmark system verify the advantages of the proposed method over several recent multi-agent DRL-based algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Carbon flow through energycane agroecosystems established post-intensive agriculture

As part of an integrated energy and climate system, biomass production for bioenergy based on the tropical perennial C4 grass energycane can both offset fossil fuels and store soil carbon (C). We measured energycane yields, root biomass, soil C pools, and soil C stocks in a 4 year field trial and modeled C flow from plants to soils in the surface layer of no-till energycane planted after more than a century of intensive sugarcane agriculture. Aboveground yields ranged from 16.7 to 19.0 Mg C/ha over the 4 year trial. Although total C stocks did not significantly differ in the surface layer (approx. 0–20 cm) during the study, C in free and occluded light fractions decreased, whereas C in the mineral-rich dense fraction increased over 4 years. Belowground system inputs, estimated from measurements and informed by convergence in the final soil fraction model, were set to 2.5 Mg C ha -1 year -1 . With this input value, we estimated that surface soils retained photosynthetically fixed C predominantly within the mineral-associated organic matter pool for a mean and median transit time of 177 and 110 years, respectively. Although we did not model C flow to deep soil layers (approx. 0–100 cm), observed C accumulation (11.4 Mg C ha -1 year -1 ) and root growth down to 120 cm suggest that soil processes and resulting C sequestration at the surface are likely to persist deeper into the soil profile. Energycane, as a strong candidate for climate change mitigation and land degradation remediation, showed high biomass yields and allocation of resources to roots, with sequestered soil C expected to persist for over a century.

09 BIOMASS FUELS↗
DOE OSTI2022

SNF1-related protein kinase 1 represses Arabidopsis growth through post-translational modification of E2Fa in response to energy stress

Cellular sugar starvation and/or energy deprivation serves as an important signaling cue for the live cells to trigger the necessary stress adaptation response. When exposed to cellular energy stress (ES) conditions, the plants reconfigure metabolic pathways and rebalance energy status while restricting vegetative organ growth. Despite the vital importance of this ES-induced growth restriction, the regulatory mechanism underlying the response remains largely elusive in plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

CALCIUM‐DEPENDENT PROTEIN KINASE32 regulates cellulose biosynthesis through post‐translational modification of cellulose synthase

Summary Cellulose is an essential component of plant cell walls and an economically important source of food, paper, textiles, and biofuel. Despite its economic and biological significance, the regulation of cellulose biosynthesis is poorly understood. Phosphorylation and dephosphorylation of cellulose synthases (CESAs) were shown to impact the direction and velocity of cellulose synthase complexes (CSCs). However, the protein kinases that phosphorylate CESAs are largely unknown. We conducted research in Arabidopsis thaliana to reveal protein kinases that phosphorylate CESAs. In this study, we used yeast two‐hybrid, protein biochemistry, genetics, and live‐cell imaging to reveal the role of calcium‐dependent protein kinase32 (CPK32) in the regulation of cellulose biosynthesis in A. thaliana . We identified CPK32 using CESA3 as a bait in a yeast two‐hybrid assay. We showed that CPK32 phosphorylates CESA3 while it interacts with both CESA1 and CESA3. Overexpressing functionally defective CPK32 variant and phospho‐dead mutation of CESA3 led to decreased motility of CSCs and reduced crystalline cellulose content in etiolated seedlings. Deregulation of CPKs impacted the stability of CSCs. We uncovered a new function of CPKs that regulates cellulose biosynthesis and a novel mechanism by which phosphorylation regulates the stability of CSCs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Detecting Short Circuits: Post Accident Electric Vehicle Battery Safety Check

Fast and accurate detection of soft short circuits (SCs) in the battery packs of damaged electric vehicles is needed by first responders and mechanics to mitigate the potential risk from battery fires that may occur hours, days, or weeks after an accident. Here, this paper presents an SC-detection algorithm for potentially damaged lithium-ion batteries that works quickly and without a priori knowledge of the battery-pack chemistry, capacity, state of charge, or state of health. The proposed universal SC-detection algorithm is designed to be implemented on an inexpensive handheld device that can connect to and monitor the voltages of all cells in a pack. Transient filtering and linear-quadratic state observation provide estimates of normalized SC current for every cell in the pack. Cells with SC-current estimates outside a sigma-based threshold are detected. Simulations, experiments, and electric vehicle (EV) crash data are used to verify the speed, sensitivity, and accuracy of the method, demonstrating 96% accurate detection of 0.0027 C SCs in under 1 h for 5S cell groups in the lab and no false positives for crashed Volkswagen, Chevrolet, and Tesla vehicles without SCs.

25 - ENERGY STORAGE↗
DOE OSTI2020

Post-Irradiation Evaluation of Eurofer97 Fracture Toughness Using Miniature Multinotch Bend Bar Specimens

In this study, we performed fracture toughness characterization of ten neutron-irradiated Eurofer97 variants using precracked miniature multi-notch bend bar (M4CVN) specimens based on the Master Curve method in the ASTM E1921 standard. The neutron irradiation was performed in the flux trap position of the High Flux Isotope Reactor (HFIR) of the Oak Ridge National Laboratory (ORNL) with the nominal irradiation temperature of 300°C and irradiation dose of 2.5 displacements per atom (dpa). Depending on the irradiation temperature and materials, we observed different degrees of irradiation hardening and embrittlement for ten Eurofer97 variants. The upper shift in the Master Curve reference temperature T0Q vs. the increase in Vickers microhardness values showed a liner relationship for only a few materials indicating different irradiation responses of the Eurofer97 variants.

Chen, Xiang↗
DOE OSTI2020

Accelerating Scientific Computing in the Post-Moore’s Era

Novel uses of graphical processing units for accelerated computation revolutionized the field of high-performance scientific computing by providing specialized workflows tailored to algorithmic requirements. As the era of Moore’s law draws to a close, many new non–von Neumann processors are emerging as potential computational accelerators, including those based on the principles of neuromorphic computing, tensor algebra, and quantum information. While development of these new processors is continuing to mature, the potential impact on accelerated computing is anticipated to be profound. We discuss how different processing models can advance computing in key scientific paradigms: machine learning and constraint satisfaction. Significantly, each of these new processor types utilizes a fundamentally different model of computation, and this raises questions about how to best use such processors in the design and implementation of applications. While many processors are being developed with a specific domain target, the ubiquity of spin-glass models and neural networks provides an avenue for multi-functional applications. Furthermore, this also hints at the infrastructure needed to integrate next-generation processing units into future high-performance computing systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Post Irradiation Examination Dislocation Defect Detection Software

This software provides dislocation-type defect identification and segmentation using a standard open source computer vision model, YOLOv8, that leverages transfer learning to create a highly effective dislocation defect quantification tool while using only a minimal number of expert annotated micrographs for training. This model demonstrates the ability to segment both dislocation lines and loops concurrently in micrographs with high pixel noise levels and on multiple alloys. It includes multiple layers of frozen layers used for transfer learning from multidisciplinary data and is extensible to alloys that are not included in the training dataset.

Anderson, MatthewW↗
DOE OSTI2025

Data for "Anti-Pdc1p Nanobody as a Genetically Encoded Inhibitor of Ethanol Production Enables Dual Transcriptional and Post-translational Controls of Yeast Fermentations"

Microbial fermentation provides a sustainable method of producing valuable chemicals. Adding dynamic control to fermentations can significantly improve titers, but most systems rely on transcriptional controls of metabolic enzymes, leaving existing intracellular enzymes unregulated. This limits the ability of transcriptional controls to switch off metabolic pathways, especially when metabolic enzymes have long half-lives. We developed a two-layer transcriptional/post-translational control system for yeast fermentations. Specifically, the system uses blue light to transcriptionally activate the major pyruvate decarboxylase PDC1 , required for cell growth and concomitant ethanol production. Switching to darkness transcriptionally inactivates PDC1 and instead activates the anti-Pdc1p nanobody, NbJRI, to act as a genetically encoded inhibitor of Pdc1p accumulated during the growth phase. This dual transcriptional/post-translational control improves the production of 2,3-BDO and citramalate by up to 100 and 92% compared to using transcriptional controls alone in dynamic two-phase fermentations. This study establishes the NbJRI nanobody as an effective genetically encoded inhibitor of Pdc1p that can enhance the production of pyruvate-derived chemicals.

metabolic engineering↗
DOE OSTI2026

Nonlinear post-compression to sub-20 fs using a single-stage multipass cell filled with ambient air

Noble gas-filled multipass cells have proven to be very effective in compressing high-energy, hundreds-of-femtoseconds pulses down to tens of femtoseconds. Molecular gases can be an attractive alternative to noble gases since they provide additional Raman nonlinearities that can be much stronger than the electronic Kerr nonlinearity and can therefore enable more spectral broadening and shorter compressed pulses. Air at atmospheric pressure offers molecular gases in their simplest format, with both easy access and no costs for implementing a gas chamber. Here we demonstrate a single-stage, air-filled multipass cell that spectrally broadens 145- μ J, 185-fs pulses with >90% throughput, with a small fraction of the output compressed to sub-20 fs using a prism-pair compressor. The multipass cell uses standard broadband mirrors without dispersion engineering and ambient air as the nonlinear medium, making it the simplest and most cost-effective solution for generating few-cycle femtosecond pulses.

47 OTHER INSTRUMENTATION↗